2 measurements taken within a single day. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 42–44 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Sept 2026, 18:22
43
no change
13 Sept 2026, 17:47
43
first reading
Engagement
20 posts held, back to 25 January 2025 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.
ERR · 30 days
69.8%
avg views ÷ 43 subscribers
Avg views / post
30.0
1 post measured
Reaction rate
16.7%
reactions ÷ views · ER floor
Posts in window
1
of 20 held
ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.
ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate.
What these figures were computed from
Window
Rolling 30 days · latest post in window 25 August 2026
Posts held
20 (25 January 2025 – 25 August 2026)
Views total
30
Reactions total
5
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
13 Sept 2026, 18:22 UTC
Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.
Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.
Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.
What this channel posts
Photos
4
Links
3
Lifetime counters from Telegram’s own channel header, read 13 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Reaction mix
37 reactions across 11 posts, in 7 distinct kinds. The most used accounts for 51.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
19
51.4%
👍
10
27.0%
🔥
3
8.11%
❤🔥
2
5.41%
✍
1
2.70%
💯
1
2.70%
🤔
1
2.70%
No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.
Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.
Coverage. Reactions were read on 12 of the 20 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 37 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 25 January 2025 to 25 August 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.
Вовлеченность — не просто так…
Кто со мной знаком лично, знает, что я довольно скептически отношусь к метрикам, которые слабо влияют на ключевые бизнес-результаты. Поэтому, когда начала заниматься исследованием методологии вовлеченности, одним из основных вопросов был: зачем мы ее замеряем? На что влияют вовлеченность, eNPS, приверженность к компании?
Каких-то весомых исследований, которые доказывают сильную связь …
Спасибо за ваши голоса 😍
А пока мы делаем внутри командные встречи, где обсуждаем как вовлеченность диагностирует где ломается эффективность команды. И знаете что?
Дискуссия работает, а на вовлеченность, хоть и со скрипом, начали смотреть приземленно
Вопрос недели у меня:
Стоит ли говорить о вовлеченности, когда компания в большой организационной трансформации?
Интересно, что делятся мнения примерно на 2 аудитории:
Первая и самая большая (в моем окружении около 90%) говорит о том, что вовлеченность - показатель, который измеряет состояние рабочей среды и когда среду трясет и все меняется нечего там измерять.
«Как мы будем спрашивать о вовлеченности, когда всех …
Почти сто лет назад Алексей Гастев предложил удивительно современную схему организации работы.
План → Подготовка → Установка → Режим → Выдержка.
Если переложить эту схему на современную офисную реальность, получится довольно точное описание того, почему мы устаём и теряем продуктивность.
План.Сначала нужно понять, что именно должно быть сделано. Не открыть ноутбук и начать отвечать на всё подряд, а определить резу…
Привет, неравнодушные!
Вопросы приоритезации все острее стоят на повестке дня. У меня так точно
Особенно, если это касается ресурсов на автоматизацию ручного труда.
Людей не хватает, бюджета на дополнительных нет, а значит нужно делать только самое-самое важное...
И тут начинается игра на шахматной доске: как понять что самое важное, если это еще и с фокусом на изменение и развитие опыта сотрудника?
Что вижу чаще все…
Путь от исследований до реально реализованных проектов тернист, извилист и непредсказуем…
Я имею большой опыт работы в инхаус и в консалтинге на разных позициях, но только сейчас, когда мы работаем в плотной связке с командой разработки начинаю понимать как на самом деле надо отдавать результаты исследований, чтобы не получились костры рабынь
1. Общей презентации мало. Нужны все детали и сгруппированные по гипотезам…
6 советов себе при внедрении системы непрерывного слушания:
1. все проще, чем кажется: измеряй сначала то, что уже можно измерить
2. измеряй опыт через 3 призмы: точки контакта сотрудника с компанией (тот самый EJM), процессы, цифровые сервисы. Это даст более качественную и полную картину того, что происходит
3. не смотри на одну цифру, анализируй разные персоны, которые есть в компании
4. не старайся сразу делиться…
Наверное, немного компаний может похвастаться тем, что последовательно и всесторонне оценивают опыт сотрудника. Мне повезло, что я работаю именно в такой компании (или компании повезло со мной, что развиваю систему непрерывного слушания) и могу отслеживать что происходит с опытом сотрудника в динамике.
и вот несколько наблюдений:
1. сам по себе замер и динамичное отслеживание HR этой метрики работает. В отличие от др…
Давайте обсуждать.
Есть еще интересное про гибридную работу и то, как по-разному этот опыт воспринимают работодатели и сотрудники. Тут могу поделиться своими наработками и поспорить с исследованием CISCO. Отмечайте реакциями, если интересно
❤6
Showing the 12 most recent of 20 posts we hold for @focusxp. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.
Polls
The poll we hold for this entry, as Telegram rendered it when we read the post. A poll’s figures keep moving after that, so each one is dated.
Что за дурацкие вопросы? Эта вовлеченность никому не нужна на самом деле9%
Shares as published. No per-option vote count is published by Telegram, so none is shown.
Percentages only — there are no per-option vote counts here, because Telegram publishes none. The public post preview gives each option’s share and a single voter total, and nothing else. Multiplying one by the other would produce a per-option tally that looks measured and is not: the shares are rounded to whole numbers before we ever see them. We print what was published and leave the column that does not exist empty.
The shares need not add up to 100. Rounding alone puts many polls at 99 or 101. A poll that allows more than one answer per voter runs well past 100 by design, and several here do. The bars are drawn against a fixed 100% track at each option’s own percentage rather than normalised to the total, so a poll that exceeds it shows that it does instead of being quietly rescaled.
Read from the 20 most recent posts we hold, published 25 January 2025 to 25 August 2026. Telegram labels each poll by kind — an anonymous poll, a quiz, a closed set of final results — and that label is reproduced rather than paraphrased.
Mentions
Named by 1 registered channel — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Cite this entry
A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 13 September 2026 — this
entry's latest reading, not the date you are reading this.
“На опыте” (@focusxp), 43 subscribers as measured 13 September 2026. Telegram Register, tgregister.com/channel/focusxp.
Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.